refresh

Trending Companies

Trending

Jobs

JobsMastercard

Data Engineer-2

Mastercard

Data Engineer-2

Mastercard

Pune, India

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Generous paid time off and holidays

Comprehensive health, dental, and vision insurance

Flexible work arrangements

Competitive salary and equity package

Healthcare

Flexible Hours

Equity

Required Skills

React

TypeScript

JavaScript

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Data Engineer-2

Overview:

We are the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities.

  • Our team within Mastercard
  • Services:
    The Services org is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the world's largest organizations to make multi-million dollar decisions and grow their businesses. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services.
    Data Analytics and AI Solutions (DAAI) Program:
    Within the D&S Technology Team, the DAAI program is a relatively new program that is comprised of a rich set of products that provide accurate perspectives on Portfolio Optimization, and Ad Insights. Currently, we are enhancing our customer experience with new user interfaces, moving to API and web application-based data publishing to allow for seamless integration in other Mastercard products and externally, utilizing new data sets and algorithms to further analytic capabilities, and generating scalable big data processes.
    We are looking for an innovative software engineering lead who will lead the technical design and development of an Analytic Foundation. The Analytic Foundation is a suite of individually commercialized analytical capabilities (think prediction as a service, matching as a service or forecasting as a service) that also includes a comprehensive data platform. These services will be offered through a series of APIs that deliver data and insights from various points along a central data store. This individual will partner closely with other areas of the business to build and enhance solutions that drive value for our customers.
    Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features. The range of work you will encounter varies from building intuitive, responsive UIs to designing backend data models, architecting data flows, and beyond. There are no rigid organizational structures, and each team uses processes that work best for its members and projects.
    Here are a few examples of products in our space:
    Portfolio Optimizer (PO) is a solution that leverages Mastercard's data assets and analytics to allow issuers to identify and increase revenue opportunities within their credit and debit portfolios.
    Ad Insights uses anonymized and aggregated transaction insights to offer targeting segments that have high likelihood to make purchases within a category to allow for more effective campaign planning and activation.
    Help found a new, fast-growing engineering team!

Position Responsibilities:

As a Data Engineer within DAAI, you will:
Play a large role in the implementation of complex features
Push the boundaries of analytics and powerful, scalable applications
Build and maintain analytics and data models to enable performant and scalable products
Ensure a high-quality code base by writing and reviewing performant, well-tested code
Mentor junior engineers and teammates
Drive innovative improvements to team development processes
Partner with Product Managers and Customer Experience Designers to develop a deep understanding of users and use cases and apply that knowledge to scoping and building new modules and features
Collaborate across teams with exceptional peers who are passionate about what they do

Ideal Candidate Qualifications:

4+ years of data engineering experience in an agile production environment
Experience leading the design and implementation of large, complex features in full-stack applications
Ability to easily move between business, data management, and technical teams; ability to quickly intuit the business use case and identify technical solutions to enable it

  • Experience leveraging open source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform analyses
  • High proficiency in using Python or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, Ni Fi, Scoop), SQL to build Big Data products & platforms
  • Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting
    Experience in cloud technologies like Databricks/AWS/Azure
    Strong technologist with proven track record of learning new technologies and frameworks
    Customer-centric development approach
    Passion for analytical / quantitative problem solving
    Experience identifying and implementing technical improvements to development processes
    Collaboration skills with experience working with people across roles and geographies
    Motivation, creativity, self-direction, and desire to thrive on small project teams
    Superior academic record with a degree in Computer Science or related technical field
    Strong written and verbal English communication skills #AI3

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

  • Abide by Mastercard's security policies and practices;
  • Ensure the confidentiality and integrity of the information being accessed;
  • Report any suspected information security violation or breach, and
  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

About Mastercard

Mastercard

A financial network that processes payments between banks and cardholders

10,001+

Employees

Purchase

Headquarters

$360B

Valuation

Reviews

4.1

15 reviews

Work Life Balance

4.0

Compensation

3.5

Culture

3.5

Career

3.0

Management

3.0

65%

Recommend to a Friend

Pros

Good work-life balance reputation

Competitive compensation packages

Strong benefits and perks

Cons

Recent layoffs and job insecurity

Limited negotiation flexibility on salary

No RSUs for some positions

Salary Ranges

32 data points

Junior/L3

Director

Junior/L3 · Data Engineer

5 reports

$137,800

total / year

Base

$106,000

Stock

-

Bonus

-

$107,900

$166,918

Interview Experience

7 interviews

Difficulty

3.3

/ 5

Duration

14-28 weeks

Offer Rate

29%

Experience

Positive 0%

Neutral 86%

Negative 14%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Interview

4

Behavioral Interview

5

Final Round/Super Day

6

Offer Decision

Common Questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design

Past Experience